Did You Know: The Real Profit Engine Isn’t Just Data, It’s All Data Context

Connected World Editorial Director Peggy Smedley recently sat down with Twisthink CEO Dave Moelker to get to the heart of why contextual data is so vital today and why this is truly a gamechanger for OEMs (original-equipment manufacturers) as they look to the future to compete, and deliver outcomes that outperform their most challenging competitors in a world that never sleeps, but demands provocative data insights, smart new revenue streams, and excellent winning service anywhere in the globe. And that means data context.

CW:      Why do so many predictive maintenance solutions still lack critical context?

DM:      Too many solutions were built as single-point solutions, focused on technology rather than considering the people, processes, and contextual data required to deliver the necessary business outcomes. There’s a common assumption that simply capturing machine data will generate value. In reality, data collection and predictive analytics are only the beginning of the process. To make the data and insights valuable, they need to be delivered to the right users, at the right time, in the right way, to deliver value… data needs context.

CW:      What single piece of contextual data most dramatically improves predictive accuracy?

DM:      If one stands out, it’s closed-loop service outcome data: a clean record of what failed, what actions were taken, and whether those actions resolved the issue. While raw telemetry tells you that something has changed, service outcomes tell you what that change meant. In practice, which is the difference between a model that raises a high number of nuisance alerts and one that delivers actionable predictions.

CW:      If OEMs fully leveraged service logs, warranty data, and technician notes, what new capabilities would emerge?

DM:      Leveraging this data enables a shift from predictive maintenance to predictive outcomes. Maintaining equipment is essential, but if we stop there, we miss opportunities to drive even more value across the intersection of domains, such as supply chain, product design, and customer support.

CW:      Why isn’t telematics alone enough to stay competitive in industrial IoT?

Telematics can tell me what happened, but it struggles to tell me why it happened, and most importantly, what I should do next. Organizations implementing telematics solutions into their products need to think deeply about their customers’ workflows and needs, and ensure their solutions are aligned. Providing data isn’t enough anymore. Competitive differentiation comes from turning machine data into better uptime, faster service resolution, lower total cost of ownership, and more proactive customer experience.

CW:      When OEMs “get out of the building,” what insight tends to change their perspective most?

DM:      They often realize that customers don’t care about the technology itself. End users, dealers, operators, and maintenance teams prioritize ease of use, uptime, response time, workarounds, ease of service, and the practical constraints of their day-to-day. Any effort required to install, maintain, or support your solution is taking time away from addressing the outcomes they care most about.

CW:      Where do OEM assumptions about customer needs most often diverge from reality?

DM:      The biggest gap is the complexity of real-world workflows. In B2B environments, every customer operates differently and this creates significant burdens on OEMs to deliver adaptable solutions. OEMs have two options for addressing this need. The first is to build flexible solutions that can be tailored to meet customers’ needs. The second is to build solutions that unlock so much value that customers are willing to adapt their processes. The downside of the first approach is the complexity of managing and supporting customer customization. The challenge for the second approach is doing the hard work to innovate and deliver these types of impactful solutions. While the second approach can seem harder in the near term, the long-term value unlock for the business is significant.

CW:      What data quality issues typically surface first—and why are they so impactful?

DM:      Early issues are often the unglamorous ones: inconsistent asset naming, incomplete work-order history, missing failure classifications, bad timestamps, duplicate records, and free-text technician entries that mean five different things, depending on who typed them. They matter because they break the chain between an observed condition and a verified outcome. When that linkage is weak, models produce more false positives and users’ trust erodes. Trust is the most critical factor in driving adoption. We get one opportunity to instill trust in a solution, and once it is lost, users will never come back.

CW:      What is one practical step OEMs can take immediately to strengthen their data foundation?

DM:      Standardize the service close-out process. Require every completed service event to capture the asset ID, failure mode, corrective action, replaced parts, timestamp, and resolution status in a structured format. That one step creates the labeled history most OEMs are missing and improves both analytics and field execution.

CW:      What do OEMs need to be doing to create a competitive product for the future?

DM:      They must design for outcomes, not just products. That means building products and service models around connected visibility, maintainability, closed-loop service intelligence, and a direct feedback path from the field into engineering and product management. The future competitive product is not just a smarter device; it is a physical solution paired with services that increase in value over time.

CW:      What’s the one piece of advice you would give an OEM?

DM:      Stop treating telemetry as your strategy. True competitive advantage lies in combining machine data, service data, and customer reality, and the speed at which you can turn that into better decisions. The OEMs that succeed will not be the ones with the most sensors, but the ones that learn fastest from the field, apply that learning, and continuously improve the customer experience with every interaction.

About the Author
As Twisthink’s CEO, Dave brings a unique blend of technical expertise and strategic leadership to advance what’s possible through connected product development. His roots in RF communications, embedded systems, and signal processing, combined with experience across engineering, product strategy, business development, and operations, allow him to bridge business needs with engineering possibilities to create impactful solutions for clients. Dave can be reached at: davem@twisthink.com

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